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#ask-ai
Title
# ask-ai
c

Caelan Schneider

03/04/2024, 3:41 PM
how can you override global resource definitions on a job?
s

Scout

03/04/2024, 3:41 PM
To override global resource definitions on a job, you can specify the
resource_defs
parameter when defining the job. This allows you to provide custom resource definitions for that specific job, which will take precedence over the global resources defined in the
Definitions
object. Here's an example from the documentation that illustrates how to override a global resource definition for a specific job:
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python from dagster import job, Definitions, ConfigurableResource  class MyResource(ConfigurableResource):     # Resource definition with some configuration     ...  # Define a global resource that will be used by default global_resource = MyResource(...)  # Define a job without specifying resource_defs, it will use the global resource @job def my_job_without_override():     ...  # Define a job with an overridden resource definition @job(resource_defs={"my_resource": MyResource(...)}) def my_job_with_override():     ...  # Create a Definitions object with the global resource defs = Definitions(     jobs=[my_job_without_override, my_job_with_override],     resources={"my_resource": global_resource}, )
In this example,
my_job_without_override
will use the global
MyResource
instance defined in
defs
. However,
my_job_with_override
specifies its own
resource_defs
and will use the overridden
MyResource
instance provided there. Keep in mind that if you provide a subset of the resources in
resource_defs
for a job, the job will only have access to the provided resources, and the resource dictionary is not merged with the global resources. This means that you need to ensure that all required resources for the job are provided when overriding.
c

Caelan Schneider

03/04/2024, 3:45 PM
@Scout How can I use a mix of global resources and job-level resources when defining a job?
s

Scout

03/04/2024, 3:45 PM
As of the current state of the documentation, when you define a job and specify
resource_defs
, it will replace the global resources provided to
Definitions
with the resources specified in the
resource_defs
. This means that if you want to use a mix of global resources and job-level resources, you need to explicitly include all necessary resources in the
resource_defs
when defining the job. Here's an example based on the documentation:
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python from dagster import job, op, ConfigurableResource, Definitions  class MyResource(ConfigurableResource):     # Resource definition with some configuration     ...  class MySecondResource(ConfigurableResource):     # Another resource definition     ...  # Define global resources global_resources = {     "my_resource": MyResource(...),     "my_second_resource": MySecondResource(...), }  # Define a job that uses a mix of global and job-level resources @job(resource_defs={     "my_resource": MyResource(...),  # This overrides the global resource     "my_second_resource": global_resources["my_second_resource"]  # This uses the global resource }) def my_mixed_resources_job():     ...  # Create a Definitions object with the global resources defs = Definitions(     jobs=[my_mixed_resources_job],     resources=global_resources, )
In this example,
my_mixed_resources_job
explicitly defines
my_resource
in its
resource_defs
, which overrides the global definition. It also includes
my_second_resource
from the global resources to ensure it is available to the job. It's important to note that the behavior of merging resources is not supported; you must explicitly define all resources needed by the job in the
resource_defs
if you are providing any job-level resources. If you only want to use global resources, you can omit the
resource_defs
parameter in the job definition, and the job will inherit the resources from the global
Definitions
.
c

Caelan Schneider

03/04/2024, 3:59 PM
@Scout How would you override resource on an asset job?
s

Scout

03/04/2024, 3:59 PM
To override a resource on an asset job, you can use the
resource_defs
argument when defining the job with
define_asset_job
. This allows you to specify custom resource definitions for the job that will be used when materializing the assets associated with that job. Here's an example of how you might override a resource for an asset job:
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python from dagster import define_asset_job, asset, ResourceDefinition  # Define a custom resource class MyCustomResource:     def __init__(self, config):         self.config = config  # Define an asset @asset def my_asset():     # Asset computation logic     ...  # Define an asset job with an overridden resource my_asset_job = define_asset_job(     name="my_asset_job",     selection=[my_asset],     resource_defs={         "my_custom_resource": ResourceDefinition.hardcoded_resource(MyCustomResource(config={"key": "value"}))     } )
In this example,
my_asset_job
is defined with a custom resource called
my_custom_resource
. The
ResourceDefinition.hardcoded_resource
method is used to create a resource definition with hardcoded configuration. When
my_asset_job
is executed, it will use the overridden
my_custom_resource
instead of any global resource definitions with the same key. Remember that when you override resources in this way, you need to ensure that all required resources for the job are provided. If there are other resources that the assets depend on, you must include them in the
resource_defs
as well.
c

Caelan Schneider

03/04/2024, 4:09 PM
@Scout there is no resource_defs argument in define_asset_job
s

Scout

03/04/2024, 4:09 PM
You are correct; my previous response was inaccurate. The
define_asset_job
function does not have a
resource_defs
argument. In Dagster, resources are supplied to assets, not directly to the job when using
define_asset_job
. Instead, you bind resources to assets, and those resources are then used when the asset job is executed. Here's how you can bind resources to assets:
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python from dagster import asset, ResourceDefinition, define_asset_job, with_resources  # Define a custom resource class MyCustomResource:     def __init__(self, config):         self.config = config  # Define an asset @asset(required_resource_keys={"my_custom_resource"}) def my_asset(context):     # You can access the custom resource via context.resources     my_resource = context.resources.my_custom_resource     # Asset computation logic     ...  # Create a resource definition for your custom resource my_custom_resource_def = ResourceDefinition.hardcoded_resource(MyCustomResource(config={"key": "value"}))  # Bind the resource to the asset my_asset_with_resource = with_resources([my_asset], {"my_custom_resource": my_custom_resource_def})  # Define an asset job my_asset_job = define_asset_job(     name="my_asset_job",     selection=[my_asset_with_resource] )
In this example, the
with_resources
function is used to bind the
my_custom_resource
resource to the
my_asset
asset. When
my_asset_job
is executed, it will use the resources bound to the assets included in the job. If you have a global resource that you want to override for a specific asset within a job, you would redefine the asset with the new resource binding and include that redefined asset in the job selection.
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